Assignment Task
Overview
In this assessment you will perform a statistical investigation on a dataset that you compile from GapMinder. In the statistical investigation, you will perform exploratory data analysis, a set of generated hypothesis and statistical interrogation of the hypothesises. Your report will use RStudio to generate visualisations and statistical outcomes, while your written report will communicate the interpretations of the RStudio outputs and your justifications for your statistical analysis.
Learning outcomes
Understand and apply new data science skills, knowledge, and techniques to solve problems in data science using statistical hypothesis testing:
– demonstrate sound knowledge of the basic principles that underpin sample selection, experimental design, statistical theories, data visualisation and linear modelling.
– effectively integrate and execute statistical theories and processes in RStudio.
– retrieve, analyse, synthesise, and evaluate outputs produced from RStudio.
– integrate statistical principles, methods, techniques, and tools covered in this course to plan and execute a statistical analysis.
– evaluate, synthesise, and communicate findings from statistical investigations in a form suitable for specialist and non-specialist audiences.
Tasks
There are three main tasks (1) Describing your data, both numerically and visually, (2) performing a linear regression between two variables and (3) performing a statistical investigation on a hypothesis.
I. Describing your data, both numerically and visually
In this section will describe your data, the data distributions using numerical summaries and visualisations. Be sure to include:
– The sample size of each variable
– The variables used in your analysis, and the variable type.
– Tables for relevant summary statistics.
– Any data pre-processing that was done prior to analysing your data. Pre-processing may include but is not limited to ways of handling missing data, transforming data.
– Discuss the limitations of the data
II. Linear regression between two variables
In this section, perform a linear regression between the two variables derived from step 1 in the Data section. Be sure to include:
– A visualisation of the variables used in the linear regression analysis, such as scatter plots, histograms, boxplots.
– A discussion on the statistical assumptions for the regressions analysis that you choose.
– Statistical evidence relating to the validity of the statistical assumptions
– Interpretation of the statistical output of the regression analysis
– Where appropriate support your hypothesis test with a confidence interval(s)
– A visualisation of the residuals resulting from the regression analysis
– A discussion of the residuals and any relevant statistical evidence of those residuals in relation to the assumptions of the regression analysis
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